Biology subjects

Pereira, P. M.

Publications and source records attributed to Pereira, P. M..

11 recordsLinked to original sources

bioRxiv2024

PhotoFiTT: A Quantitative Framework for Assessing Phototoxicity in Live-Cell Microscopy Experiments

Phototoxicity in live-cell fluorescence microscopy can compromise experimental outcomes, yet quantitative methods to assess its impact remain limited. Here we present PhotoFiTT (Phototoxicity Fitness Time Trial), an integrated framework combining a standardised experimental protocol with advanced image analysis to quantify light-induced cellular stress in label-free settings. PhotoFiTT leverages machine learning and cell cycle dynamics to analyse mitotic timing, cell size changes, and overall cellular activity in response to controlled light exposure. Using adherent mammalian cells, we demonstrate PhotoFiTTs ability to detect wavelength- and dose-dependent effects, showcasing that near-UV light induces significant mitotic delays at doses as low as 0.6 J/cm2, while longer wavelengths require higher doses for comparable effects. PhotoFiTT enables researchers to establish quantitative benchmarks for acceptable levels of photodamage, facilitating the optimisation of imaging protocols that balance image quality with sample health.

cell biology↗

bioRxiv2023

NanoPyx: super-fast bioimage analysis powered by adaptive machine learning

To overcome the challenges posed by large and complex microscopy datasets, we have developed NanoPyx, an adaptive bioimage analysis framework designed for high-speed processing. At the core of NanoPyx is the Liquid Engine, an agent-based machine-learning system that predicts acceleration strategies for image analysis tasks. Unlike traditional single-algorithm methods, the Liquid Engine generates multiple CPU and GPU code variations using a meta-programming system, creating a competitive environment where different algorithms are benchmarked against each other to achieve optimal performance under the user"s computational environment. In initial experiments focusing on super-resolution analysis methods, the Liquid Engine demonstrated an over 10-fold computational speed improvement by accurately predicting the ideal scenarios to switch between algorithmic implementations. NanoPyx is accessible to users through a Python library, code-free Jupyter notebooks, and a napari plugin, making it suitable for individuals regardless of their coding proficiency. Furthermore, the optimisation principles embodied by the Liquid Engine have broader implications, extending their applicability to various high-performance computing fields.

bioinformatics↗

bioRxiv2021

DeepBacs: Bacterial image analysis using open-source deep learning approaches

Deep Learning (DL) is rapidly changing the field of microscopy, allowing for efficient analysis of complex data while often out-performing classical algorithms. This revolution has led to a significant effort to create user-friendly tools allowing biomedical researchers with little background in computer sciences to use this technology effectively. Thus far, these approaches have mainly focused on analysing microscopy images from eukaryotic samples and are still underused in microbiology. In this work, we demonstrate how to use a range of state-of-the-art artificial neural-networks particularly suited for the analysis of bacterial microscopy images, using our recently developed ZeroCostDL4Mic platform. We showcase different DL approaches for segmenting bright field and fluorescence images of different bacterial species, use object detection to classify different growth stages in time-lapse imaging data, and carry out DL-assisted phenotypic profiling of antibiotic-treated cells. To also demonstrate the DL capacity to enhance low-phototoxicity live-cell microscopy, we showcase how image denoising can allow researchers to attain high-fidelity data in faster and longer imaging. Finally, artificial labelling of cell membranes and predictions of super-resolution images allow for accurate mapping of cell shape and intracellular targets. To aid in the training of novice users, we provide a purposefully-built database of training and testing data, enabling bacteriologists to quickly explore how to analyse their data through DL. We hope this lays a fertile ground for the efficient application of DL in microbiology and fosters the creation of novel tools for bacterial cell biology and antibiotic research.

microbiology↗

bioRxiv2021

Single-molecule super-resolution imaging of T-cell plasma membrane CD4 redistribution upon HIV-1 binding

The first step of cellular entry for the human immunodeficiency virus type-1 (HIV-1) occurs through the binding of its envelope protein (Env) with the plasma membrane receptor CD4 and co-receptor CCR5 or CXCR4 on susceptible cells, primarily CD4+ T cells and macrophages. Although there is considerable knowledge of the molecular interactions between Env and host cell receptors that lead to successful fusion, the precise way in which HIV-1 receptors redistribute to sites of virus binding at the nanoscale remains unknown. Here, we quantitatively examine changes in the nanoscale organisation of CD4 on the surface of CD4+ T cells following HIV-1 binding. Using single-molecule super-resolution imaging, we show that CD4 molecules are distributed mostly as either individual molecules or small clusters of up to 4 molecules. Following virus binding, we observe a local 3-to-10-fold increase in cluster diameter and molecule number for virus-associated CD4 clusters. Moreover, a similar but smaller magnitude reorganisation of CD4 was also observed with recombinant gp120. For the first time, our results quantify the nanoscale CD4 reorganisation triggered by HIV-1 on host cells. Our quantitative approach provides a robust methodology for characterising the nanoscale organisation of plasma membrane receptors in general with the potential to link spatial organisation to function.

biophysics↗

bioRxiv2020

Super-Beacons: open-source probes with spontaneous tunable blinking compatible with live-cell super-resolution microscopy

Localization based super-resolution microscopy relies on the detection of individual molecules cycling between fluorescent and non-fluorescent states. These transitions are commonly regulated by high-intensity illumination, imposing constrains to imaging hardware and producing sample photodamage. Here, we propose single-molecule self-quenching as a mechanism to generate spontaneous photoswitching independent of illumination. To demonstrate this principle, we developed a new class of DNA-based open-source Super-Resolution probes named Super-Beacons, with photoswitching kinetics that can be tuned structurally, thermally and chemically. The potential of these probes for live-cell friendly Super-Resolution Microscopy without high-illumination or toxic imaging buffers is revealed by imaging Interferon Inducible Transmembrane proteins (IFITMs) at sub-100nm resolutions.

cell biology↗

bioRxiv2019

Nuclear pores as versatile reference standards for quantitative superresolution microscopy

Quantitative fluorescence and superresolution microscopy are often limited by insufficient data quality or artifacts. In this context, it is essential to have biologically relevant control samples to benchmark and optimize the quality of microscopes, labels and imaging conditions.\n\nHere we exploit the stereotypic arrangement of proteins in the nuclear pore complex as in situ reference structures to characterize the performance of a variety of microscopy modalities. We created four genome edited cell lines in which we endogenously labeled the nucleoporin Nup96 with mEGFP, SNAP-tag or HaloTag or the photoconvertible fluorescent protein mMaple. We demonstrate their use a) as 3D resolution standards for calibration and quality control, b) to quantify absolute labeling efficiencies and c) as precise reference standards for molecular counting.\n\nThese cell lines will enable the broad community to assess the quality of their microscopes and labels, and to perform quantitative, absolute measurements.

biophysics↗

bioRxiv2018

Fix your membrane receptor imaging: Actin cytoskeleton and CD4 membrane organization disruption by chemical fixation

Single-molecule localization microscopy (SMLM) techniques allow near molecular scale resolution (~ 20nm) as well as precise and robust analysis of protein organization at different scales. SMLM hardware, analytics and probes have been the focus of a variety of studies and are now commonly used in laboratories across the world. Protocol reliability and artefact identification are increasingly seen as important aspects of super-resolution microscopy. The reliability of these approaches thus requires in-depth evaluation so that biological findings are based on solid foundations. Here we explore how different fixation approaches that disrupt or preserve the actin cytoskeleton affect membrane protein organization. Using CD4 as a model, we show that fixation-mediated disruption of the actin cytoskeleton correlates with changes in CD4 membrane organization. We highlight how these artefacts are easy to overlook and how careful sample preparation is essential for extracting meaningful results from super-resolution microscopy.

cell biology↗

bioRxiv2018

NanoJ: a high-performance open-source super-resolution microscopy toolbox

Super-resolution microscopy has become essential for the study of nanoscale biological processes. This type of imaging often requires the use of specialised image analysis tools to process a large volume of recorded data and extract quantitative information. In recent years, our team has built an open-source image analysis framework for super-resolution microscopy designed to combine high performance and ease of use. We named it NanoJ - a reference to the popular ImageJ software it was de-veloped for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatio-temporal alignment of raw data (NanoJ-Core), super-resolution image re-construction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). We expect to expand NanoJ in the future through the development of new tools designed to improve quantitative data analysis and measure the reliability of fluorescent microscopy studies.

bioinformatics↗

bioRxiv2018

Nanoscale colocalization of NK cell activating and inhibitory receptors controls signal integration

NK cell responses depend on the balance of signals from inhibitory and activating receptors. However, how the integration of antagonistic signals occurs upon NK cell-target cell interaction is not fully understood. Here, we provide evidence that NK cell inhibition via the inhibitory receptor Ly49A is dependent on its relative colocalization at the nanometer scale with the activating receptor NKG2D upon immune synapse (IS) formation. NKG2D and Ly49A signal integration and colocalization was studied using NKG2D-GFP and Ly49A-RFP-expressing primary NK cells, forming ISs with NIH3T3 target cells, with or without expression of single chain trimer (SCT) H2-Dd and an extended form of SCT H2-Dd-CD4 MHC-I molecules. Nanoscale colocalization was assessed by Forster resonance energy transfer (FRET) between NKG2D-GFP and Ly49A-RFP and measured for each synapse. In the presence of their respective cognate ligands, NKG2D and Ly49A colocalize at a nanometer scale leading to NK cell inhibition. However, increasing the size of the Ly49A ligand reduced the nanoscale colocalization with NKG2D consequently impairing Ly49A-mediated inhibition. Thus, our data shows NK cell signal integration is critically dependent on the dimensions of NK cell ligand-receptor pairs by affecting their relative nanometer-scale colocalization at the IS. Together, our results suggest the balance of NK cell signals, and NK cell responses, are determined by the relative nanoscale colocalization of activating and inhibitory receptors in the immune synapse.

immunology↗

bioRxiv2018

TMEM16F activation by Ca2+ triggers plasmalemma expansion and directs PD-1 trafficking

TMEM16F, an ion channel gated by high cytoplasmic Ca2+, is required for cell surface phosphatidylserine exposure during platelet aggregation and T cell activation. Here we demonstrate in Jurkat T cells and HEK293 cells that TMEM16F activation triggers large-scale surface membrane expansion in parallel with lipid scrambling. Following TMEM16F mediated scrambling and surface expansion, cells undergo extensive membrane shedding. The membrane compartment that expands the cell surface does not involve endoplasmic reticulum or acidified lysosomes. Surprisingly, T cells lacking TMEM16F expression not only fail to expand surface membrane, but instead rapidly internalize membrane via massive endocytosis (MEND). The T cell co-receptor PD-1 is selectively shed when TMEM16F triggers membrane expansion, while it is selectively internalized in the absence of TMEM16F. Its participation in this trafficking is determined by its single transmembrane domain. Thus, we establish a fundamental role for TMEM16F as a regulator of Ca2+-activated membrane trafficking.

cell biology↗

bioRxiv2017

NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts

Most super-resolution microscopy methods depend on steps that contribute to the formation of image artefacts. Here we present NanoJ-SQUIRREL, an ImageJ-based analytical approach providing a quantitative assessment of super-resolution image quality. By comparing diffraction-limited images and super-resolution equivalents of the same focal volume, this approach generates a quantitative map of super-resolution defects, as well as methods for their correction. To illustrate its broad applicability to super-resolution approaches we apply our method to Localization Microscopy, STED and SIM images of a variety of in-cell structures including microtubules, poxviruses, neuronal actin rings and clathrin coated pits. We particularly focus on single-molecule localisation microscopy, where super-resolution reconstructions often feature imperfections not present in the original data. By showing the quantitative evolution of data quality over these varied sample preparation, acquisition and super-resolution methods we display the potential of NanoJ-SQUIRREL to guide optimization of superresolution imaging parameters.

biophysics↗